DATA INVENTORY, WATERSHED CHARACTERIZATION & SUFFICIENT DATA

Michael Schramm

TWRI, Texas A&M AgriLife Research

Fundamentals of Developing a Water Quality Monitoring Plan

March 5, 2024

What are we covering?

  • Data Inventory: What data do you need, where to obtain it, best practices to maintain it.
  • Watershed Characterization: What is it and provide an overview of approaches.
  • Data Sufficiency: Do you have the data you need? Do you have enough data?

Inventory and Acquire Existing Data

Major steps

flowchart LR
  A(Determine data needs) --> one
  subgraph one[Create and maintain inventory]
    direction TB
    D --> B
    B(Identify available data) --> C(Locate the information)
    C --> D(Gather and organize data)
  end
  one --> E[(Data inventory)]

Determine data needs

While you are scoping and planning a project:

  • Identify stakeholder concerns
  • Identify watershed goals
  • Define conceptual models

Identify available data

  • Use existing data if/when available!
  • Assess the quality/reliability of that data.
  • Talk to organizations that have conducted projects in the area.

Locating information

What types of data will you need?

  • Watershed physical characteristics
  • Water quality
  • Streamflow
  • Climate
  • Pollutant sources

Locating information

Watershed physical characteristics

  • Watershed boundaries
  • Hydrographic/Topographic
  • Soil
  • Vegetation, wildlife, etc.

Locating information

Watershed physical characteristics

Locating information

Water quality

  • Routine water quality
  • Stormwater/runoff monitoring
  • Storm/flow biased water quality
  • Benthic and other stream surveys

Texas A&M AgriLife Marketing and Communications

Photo credit Michael Miller

Locating information

Water quality

Texas A&M AgriLife Marketing and Communications

Photo credit Michael Miller

Locating information

Streamflow

  • Daily/instantaneous streamflow
  • Inundation/tidal data

Texas A&M AgriLife Marketing and Communications

Photo credit Michael Miller

Locating information

Streamflow

Texas A&M AgriLife Marketing and Communications

Photo credit Michael Miller

Locating information

Climate

  • Precipitation
  • Temperature/solar radiation
  • Wind direction/speed

Texas A&M AgriLife Marketing and Communications

Photo credit Laura McKenzie

Locating information

Climate

Texas A&M AgriLife Marketing and Communications

Photo credit Laura McKenzie

Locating information

Pollution Sources

  • Permitted discharges
  • Non-permitted sources

Photo credit Ryan Gerlich (Texas A&M AgriLife Extension)

Locating information

Pollution Sources

Photo credit Ryan Gerlich (Texas A&M AgriLife Extension)

Gather and organize data

Basic Principles:

  • Create a project specific data folder or database.
  • Maintain living project documentation.
  • Use data exploration and summary methods to get a “picture” of the data.

Gather and organize data

Documentation should identify:

  • Types of data (monitoring, geographic)
  • Source
  • Quality
  • Representativeness
  • Spatial coverage
  • Temporal coverage
  • Data gaps
  • Units and variable names

Your QAPP is a good starting point.

Gather and organize data

Best practices:

  • Consistent terminology and file naming (ex. Nitrate as nitrogen, NO3-N, or nitrate…).
  • Standardized dates (highly suggest YYYY-MM-DD formatting).
  • Use non-proprietary files where possible (plain-text, csv, etc.).
  • What are your data storage practices?

Licensed under Creative Commons CC BY-NC 2.5 DEED

Image: https://xkcd.com/1459/

Gather and organize data

Spreadsheet best practices:

  • No empty cells: specify no value, NA, zero, infinity, etc.
  • One value per cell.
  • Do not use font color, cell color, or comments, as data.

Data Organization in Spreadsheets: https://doi.org/10.1080/00031305.2017.1375989

Watershed Characterization

Photo courtesy of Ed Rhodes

What is a Watershed Characterization?

An assessment of past and current conditions within a watershed to support water quality management decisions

What is a Watershed Characterization?

Can have different objectives:

  • Is there a (or where is the) water quality problem?
  • Compare and define current and desired conditions.
  • Estimate allowable loadings for point source permits or TMDLs
  • Evaluate and recommend best management practices
  • Assess trends or changes in water quality

(not an exhaustive list…)

How do we do it?

Depends on our objectives!

Objectives determine the statistical design and data (monitoring requirements)

General approaches

  • Reconnaissance
  • Plot studies
  • Watershed(s) study

Reconnaissance

Objective: Identify if or where there is a water quality problem.

  • AKA routine or ambient water quality
  • Provides a snapshot of water quality at a given point in time
  • Limited statistical application (summary statistics or probability of exceedance)
  • TCEQ assessments manual provides baseline methods for comparison.

Reconnaissance

Advantages:

  • You might already have enough data (CRP monitoring)
  • Large spatial coverage
  • Useful to pinpoint problematic areas

Reconnaissance

Disadvantages:

  • Biased towards baseflows
  • Possibly low sampling frequency in existing data
  • Sampling locations are biased

Plot studies

Objective: Evaluate differences in conditions or treatments

Experimental trials on multiple plots involving treatment and control replicates. Treatments are small plots where runoff can be routed to a single measurement point per treatment.

Image USDA NRCS (2003)

Plot studies

Often used to evaluate the impact of BMPs on runoff quality.

Advantages:

  • Well designed experiments have strong statistical power (reliability for detecting true effects)
  • Ability to control for environmental conditions

Plot studies

Disadvantages:

  • Cost
  • Conditions may not represent real world conditions
  • Results are sometimes (often?) condition specific

Plot studies

TWRI

Photo credit Jason Gerlich

Watershed studies

Objective: Evaluate Best Management Practices (BMPs), assess trends.

Multiple potential study designs:

Design Causal factors
Single watershed - before/after BMPs, Climate
Single watershed - upstream/downstream BMP, within watershed factors
Paired watershed - BACI BMP

Single watershed

Objective: Evaluate conditions before and after implementation, or trend analysis.

  • Single monitoring site at the outlet of a watershed.
  • Relatively inexpensive.
  • Difficult to separate effects due to changes climate or other watershed changes.

Single watershed (before/after implementation.)

Image USDA NRCS (2003)

Single watershed

Objective: Evaluate conditions before and after implementation, or trend analysis.

  • Monitoring before and after implementation.
  • Monitor upstream and downstream of implementation.
  • Accounts for some differences within the watershed.
  • Disadvantage, downstream measurements are not fully independent of the upstream measurements.

Single watershed (above/below implementation.)

Image USDA NRCS (2003)

Paired watershed

Objective: Evaluate conditions before and after implementation, or trend analysis.

  • Monitor before and after in calibration and treatment watersheds
  • Two or more watersheds
  • One watershed always serves as a control

Single watershed (above/below implementation.)

Image USDA NRCS (2003)

Paired watershed

Advantages:

  • Can be statistically powerful.
  • Can evaluate multiple treatments.
  • Helps control for environmentally induced variation not associated with treatment.
  • Statistical independence between treatment/pre-treatment measurements.
  • Regionally relevant results.

Paired watershed

Disadvantage:

  • Requires long study period.
  • Lag effects can be gradual masking difference with control (Meals, Dressing, and Davenport 2010).
  • Can be hard to find two watersheds that won’t have any other distrubrances for the entire study period.
  • Logistics.

Sufficient data

Depends on:

  • Statistical design
  • Variability of measurement parameters
  • Relevent effect size

Sufficient data

Things to consider:

  • Adequate number of sites
  • Adequate number of samples
  • Frequency of samples
  • Monitoring duration

Sufficient data

Available tools:

  • TCEQ assessment criteria (for ambient water quality)
  • Statistical power analysis

Additional theme classes

Some extra things you can do with the txwri-revealjs theme

Special classes for emphasis

  • .alert class for default emphasis, e.g. important note.
  • .fg class for custom colour, e.g. important note.
  • .bg class for custom background, e.g. important note.

Components

Citations

Citations follow the standard Quarto format and be sourced from BibLaTex, BibTeX, or CLS files. For example:

Components

Blocks

Quarto provides dedicated environments for theorems, lemmas, and so forth.

But in presentation format, it’s arguably more effective just to use a Callout Block.

Regression Specification

The main specification is as follows:

\[ y_{it} = X_{it} \beta + \mu_i + \varepsilon_{it} \]

Components

Multicolumn I: Text only

Column 1

Here is a long sentence that will wrap onto the next line as it hits the column width, and continue this way until it stops.

Column 2

Some other text in another column.

A second paragraph.

Multicolumn support is very flexible and we can continue with a single full span column in the same slide.

Components

Multicolumn II: Text and figures

  • A point about the figure that is potentially important.
  • Another point about the figure that is also potentially important.

Note that sub- and multi-panel figures are also natively supported by Quarto. See here.

Components

Multicolumn III: Code and output

palette("Classic Tableau")

par(
  family = "HersheySans",
  las = 1, pch = 19, cex = 1.5
)

pairs(
  iris[,1:4],
  col=iris$Species
)
Figure 1: Pairwise scatterplot

Figures

Figure

Photo courtesy of Ed Rhodes

Figure

Full-size Figures

You can use the {.background-image} container environment to completely fill the slide background with an image.

Ideally, your figure will be the same aspect ratio as the screen that you’re presenting on.

  • This can be a bit tricky because of the dynamic nature of reveal.js / HTML. But it’s probably something close to 16:9.
  • Aspect ratio can also matter for a regular full-frame images (previous slide).

Contact us

We’d love to talk about all things water

References

Biddle, Jennifer C. 2017. “Improving the Effectiveness of Collaborative Governance Regimes: Lessons from Watershed Partnerships.” Journal of Water Resources Planning and Management 143 (9): 04017048. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000802.
Helsel, Dennis R, Robert M Hirsch, Karen R. Ryberg, Stacey A. Archfield, and E J Gilroy. 2020. Statistical Methods in Water Resources: U.S. Geological Survey Techniques and Methods, Book 4, Chapter A3. Reston, VA: USGS. https://doi.org/10.3133/tm4a3.
Meals, Donald W., Steven A. Dressing, and Thomas E. Davenport. 2010. “Lag Time in Water Quality Response to Best Management Practices: A Review.” Journal of Environment Quality 39 (1): 85. https://doi.org/10.2134/jeq2009.0108.
Schramm, Michael, Anna Gitter, and Lucas Gregory. 2022. “Total Maximum Daily Loads and Escherichia Coli Trends in Texas Freshwater Streams.” Journal of Contemporary Water Research & Education 176 (1): 36–49. https://doi.org/10.1111/j.1936-704X.2022.3374.x.
USDA NRCS. 2003. “National Water Quality Handbook Part 614.” USDA NRCS. https://archive.epa.gov/water/archive/web/pdf/stelprdb1044775.pdf.

Extra slides

Types of data

Qualitative, quantitative, geospatial, temporal, etc.

Qualitative data

  • Historic documentation (newspaper articles, interviews)
  • Some types of metadata
  • Photographs
  • Comments field in SWQM data

Qualitative data

  • Provides sense of place
  • Why and when things changes

Spatial data

  • Remotely sensed gridded data Primarily land cover and elevation

Spatial data

  • Modeled gridded data Precipitation, ET/PET, solar radiation etc.

Useful inputs for watershed models (SWAT, etc.)

Spatial data

  • Topological data

Primarily stream networks and associated waterbodies

Quantitative data

Primarily interested in: - Streamflow/discharge - Discrete or continuous water quality